A comprehensive analysis of gene expression evolution between humans and mice.

Wang Y, Rekaya R - Evol. Bioinform. Online (2009)

Bottom Line:
In this study, gene expression patterns were compared between human and mouse genomes using two published methods.The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation.Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.

ABSTRACTEvolutionary changes in gene expression account for most phenotypic differences between species. Advances in microarray technology have made the systematic study of gene expression evolution possible. In this study, gene expression patterns were compared between human and mouse genomes using two published methods. Specifically, we studied how gene expression evolution was related to GO terms and tried to decode the relationship between promoter evolution and gene expression evolution. The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation. The more conserved gene expression in some biological processes than is expected in a purely neutral model reveals negative selection on gene expression. However, fast evolving genes mainly support the neutrality of gene expression evolution, and (2) gene expression conservation is positively but only slightly correlated with promoter conservation based on a motif-count score of the promoter alignment. Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.

f2-ebo-2009-081: Comparison of the motif-count scores between conserved expression and diverged expression.

Mentions:
Scores based on global alignment, local alignment and motif-count for all orthologs were calculated. Their correlations with gene expression conservations were 0.014 (P value = 0.3772), 0.016 (P value = 0.3087) and 0.055 (P value = 0.0006525), respectively using procedure I; the correlations from procedure II were 0.025 (P value = 0.1218), 0.030 (P value = 0.06608) and 0.040 (P value = 0.01205). With both procedures, the motif-count score method resulted in a slightly positive and significant correlation between promoter conservation and gene expression conservation. The increase of promoter-expression correlation using our proposed motif-count scores suggests it has improved in describing promoter conservation. To reduce the effects of noise in microarray data, we retrieved the most reliable conserved expression (top 10% ri) and diverged expression (bottom 10% ri) for analysis. An obvious decrease in motif-count scores from conserved expression to diverged expression is seen in Figure 2 (P values of two sample t test are 0.00289 and 0.003665 for procedure I and II, respectively). The promoter-expression correlations based on these reliable expression patterns were 0.103 (P value = 0.004152) and 0.122 (P value = 0.0006919) using procedures I and II, respectively, indicating a reasonable predictive power of motif-count scores to determine the variability in expression conservation.

f2-ebo-2009-081: Comparison of the motif-count scores between conserved expression and diverged expression.

Mentions:
Scores based on global alignment, local alignment and motif-count for all orthologs were calculated. Their correlations with gene expression conservations were 0.014 (P value = 0.3772), 0.016 (P value = 0.3087) and 0.055 (P value = 0.0006525), respectively using procedure I; the correlations from procedure II were 0.025 (P value = 0.1218), 0.030 (P value = 0.06608) and 0.040 (P value = 0.01205). With both procedures, the motif-count score method resulted in a slightly positive and significant correlation between promoter conservation and gene expression conservation. The increase of promoter-expression correlation using our proposed motif-count scores suggests it has improved in describing promoter conservation. To reduce the effects of noise in microarray data, we retrieved the most reliable conserved expression (top 10% ri) and diverged expression (bottom 10% ri) for analysis. An obvious decrease in motif-count scores from conserved expression to diverged expression is seen in Figure 2 (P values of two sample t test are 0.00289 and 0.003665 for procedure I and II, respectively). The promoter-expression correlations based on these reliable expression patterns were 0.103 (P value = 0.004152) and 0.122 (P value = 0.0006919) using procedures I and II, respectively, indicating a reasonable predictive power of motif-count scores to determine the variability in expression conservation.

Bottom Line:
In this study, gene expression patterns were compared between human and mouse genomes using two published methods.The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation.Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.

ABSTRACTEvolutionary changes in gene expression account for most phenotypic differences between species. Advances in microarray technology have made the systematic study of gene expression evolution possible. In this study, gene expression patterns were compared between human and mouse genomes using two published methods. Specifically, we studied how gene expression evolution was related to GO terms and tried to decode the relationship between promoter evolution and gene expression evolution. The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation. The more conserved gene expression in some biological processes than is expected in a purely neutral model reveals negative selection on gene expression. However, fast evolving genes mainly support the neutrality of gene expression evolution, and (2) gene expression conservation is positively but only slightly correlated with promoter conservation based on a motif-count score of the promoter alignment. Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.